Arize AI

Phoenix is an open-source AI observability platform developed by Arize for experimenting with, evaluating, and troubleshooting LLM applications and agents. It traces application runtime with OpenTelemetry-based instrumentation, supports response and retrieval evaluations, and provides versioned datasets, experiment tracking, prompt management, and a playground for comparing models, adjusting parameters, and replaying traced calls. Phoenix also includes PXI, an AI engineering agent for debugging traces and iterating on prompts, plus a remote MCP server for querying traces, datasets, and experiments from MCP clients. It can run locally, in containers, through Kubernetes and Helm, or in the cloud, and is distributed through the `arize-phoenix` Python package, Conda, Docker images, and related TypeScript and Python packages.

AgentOps is an open-source observability and developer-tools platform for building, evaluating, and monitoring AI agents. Its Python SDK records agent sessions and LLM calls for dashboard-based session replays, step-by-step execution graphs, debugging, analytics, cost tracking, and benchmarking. Developers instrument code with decorators for sessions, agents, operations, tasks, and workflows; these support nested span hierarchies, input and output recording, exception handling, asynchronous functions, generators, and custom attributes. The SDK provides integrations with agent frameworks and LLM systems including CrewAI, AG2/AutoGen, Agno, LangGraph, and the OpenAI Agents SDK, and the platform can be self-hosted with its dashboard and API backend. The app is released under the MIT license.

Hyperagent is an AI agent platform for assigning work to a fleet of agents that research, build, deliver and maintain outputs using an organization's data, tools and working style. Its agents operate through real browsers and shells, can search, code, make decisions and generate artifacts such as live websites, videos, presentations, documents and dashboards. Agents run in individual computing environments, expose their execution as it happens, and can learn new memories and skills over time. Work is delivered through Slack, email, Telegram, webhooks or scheduled runs, and agents are deployed and managed from a central command center.

Agently is an AI Work OS that integrates with a company's software stack to build a centralized "company brain" and deploy autonomous agents to perform tasks and workflows. The platform describes an orchestration component named Jarvis that coordinates those agents across the stack.

Anthropic is an AI research and deployment company founded by former OpenAI researchers (including Dario Amodei). It develops large language models such as Claude and focuses on AI safety research and commercial model deployments.